2018-2065 estimation data set of key elements of future water cycle in Arctic main river regions with 10 km resolution

This product provides the monthly runoff, evapotranspiration and soil water of major Arctic river basins in 2018-2065 based on the land surface model Vic. The spatial accuracy is 10km. Major Arctic river basins include Lena, Yenisey, ob, Kolyma, Yukon and Mackenzie basins. According to the rcp2.6 (low emission intensity) and rcp8.5 (high emission intensity) scenario results provided by the ipsl-cm5a-lr model in cmip5 in the fifth assessment report of IPCC, the future climate scenario driving data applicable to the Arctic region of 0.1 ° is obtained through statistical downscaling. Using the calibrated land surface hydrological model Vic on a global scale, based on the future climate scenario driven data of 0.1 °, the monthly time series of runoff, soil water and evapotranspiration of the Arctic River Basin in the middle of this century under future climate change are estimated.

0 2022-09-01

Network of soil temperature and moisture on the Pali (2015-2021)

The soil temperature and moisture observation network is located south of Tibetan Plateau, with an average elevation of 4,486 meters, providing soil moisture, soil temperature and freeze-thaw measured datasets. Data content (data file, table name, and observation indicators included) : (1) Number of sites: 25 observation sites (2) observation variables: (soil moisture and soil temperature) (3) Observation depths: (0-5, 10, 20 and 40 cm) (4) Geographic coverage: 27.7°-28.1°N; 89.1°-89.4°E (5) Spatial resolution: passive microwave satellite pixel (0.3°) (6) Temporal resolution: 30 min resolution (7) Soil moisture measurement accuracy and resolution: ± 2% VWC and 0.1% VWC. Data content field description: (1) Variable 1-6: Date (Integer: yyyy-mm-dd-hh-mm-ss; UTC+8) (2) Variable 7-34: Observational data values at each site (real, missing value: -99.00) (3) Soil moisture(SM): %vol(m³/m³) (4) Soil temperature(ST): ℃ Data correction and quality control: The 30 min resolution temperature data are the direct sampling data after quality control, and the soil moisture volume content is the correction value based on the soil moisture measurement by the drying method.

0 2022-08-07

Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (an observation system of Meteorological elements gradient of Alpine meadow and grassland ecosystem Superstation, 2021)

This dataset includes data recorded by the Qinghai Lake integrated observatory network obtained from an observation system of Meteorological elements gradient of the Alpine meadow and grassland ecosystem Superstation from January 1 to October 9 in 2021. The site (98°35′41.62″E, 37°42′11.47″N) was located in the alpine meadow and alpine grassland ecosystem, near the SuGe Road in Tianjun County, Qinghai Province. The elevation is 3718m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP155; 3, 5, 10, 15, 20, 30, and 40 m, towards north), wind speed and direction profile (windsonic; 3, 5, 10, 15, 20, 30, and 40 m, towards north), air pressure (PTB110; 3 m), rain gauge (TE525M; 10m of the platform in west by north of tower), four-component radiometer (CNR4; 6m, towards south), two infrared temperature sensors (SI-111; 6 m, towards south, vertically downward), photosynthetically active radiation (PQS1; 6 m, towards south, each with one vertically downward and one vertically upward, soil heat flux (HFP01; 3 duplicates below the vegetation; -0.06 m), soil temperature profile (109; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m), soil moisture profile (CS616; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m). The observations included the following: air temperature and humidity (Ta_3 m, Ta_5 m, Ta_10 m, Ta_15 m, Ta_20 m, Ta_30 m, and Ta_40 m; RH_3 m, RH_5 m, RH_10 m, RH_15 m, RH_20 m, RH_30 m, and RH_40 m) (℃ and %, respectively), wind speed (Ws_3 m, Ws_5 m, Ws_10 m, Ws_15 m, Ws_20 m, Ws_30 m, and Ws_40 m) (m/s), wind direction (WD_3 m, WD_5 m, WD_10 m, WD_15 m, WD_20 m, WD_30m, and WD_40 m) (°), precipitation (rain) (mm), air pressure (press) (hpa), infrared temperature (IRT_1 and IRT_2) (℃), photosynthetically active radiation of upward and downward (PAR_D_up and PAR_D_down) (μmol/ (s m-2)), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m^2), soil heat flux (Gs_1, Gs_2, and Gs_3) (W/m^2), soil temperature (Ts_5cm、Ts_10cm、Ts_20cm、Ts_40cm、Ts_80cm、Ts_120cm、Ts_200cm、Ts_300cm、Ts_400cm) (℃), soil moisture (Ms_5cm、Ms_10cm、Ms_20cm、Ms_40cm、Ms_80cm、Ms_120cm、Ms_200cm、Ms_300cm、Ms_400cm) (%, volumetric water content). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2018/8/31 10:30. Moreover, suspicious data were marked in red.

0 2022-06-29

Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (an observation system of Meteorological elements gradient of Subalpine shrub, 2021)

This dataset includes data recorded by the Qinghai Lake integrated observatory network obtained from an observation system of Meteorological elements gradient of the Subalpine shrub from January 1 to October 13, 2021. The site (100°6'3.62"E, 37°31'15.67") was located in the subalpine shrub ecosystem, near the Gangcha County, Qinghai Province. The elevation is 3495m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP155; 3, 5 and 10 m, towards north), wind speed and direction profile (windsonic; 3, 5 and 10 m, towards north), air pressure (PTB110; 3 m), rain gauge (TE525M; 2 m of the platform in west by north of tower), four-component radiometer (CNR4; 6m, towards south), two infrared temperature sensors (SI-111; 6 m, towards south, vertically downward), photosynthetically active radiation (PQS1; 6 m, towards south, each with one vertically downward and one vertically upward, soil heat flux (HFP01; 3 duplicates below the vegetation; -0.06 m), soil temperature profile (109; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m), soil moisture profile (CS616; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m). The observations included the following: air temperature and humidity (Ta_3 m, Ta_5 m, and Ta_10 m; RH_3 m, RH_5 m, and RH_10 m) (℃ and %, respectively), wind speed (Ws_3 m, Ws_5 m, and Ws_10 m) (m/s), wind direction (WD_3 m, WD_5 m and WD_10 m) (°), precipitation (rain) (mm), air pressure (press) (hpa), infrared temperature (IRT_1 and IRT_2) (℃), photosynthetically active radiation of upward and downward (PAR_D_up and PAR_D_down) (μmol/ (s m-2)), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m^2), soil heat flux (Gs_1, Gs_2, and Gs_3) (W/m^2), soil temperature (Ts_5cm、Ts_10cm、Ts_20cm、Ts_40cm、Ts_80cm、Ts_120cm、Ts_200cm、Ts_300cm、Ts_500cm) (℃), soil moisture (Ms_5cm、Ms_10cm、Ms_20cm、Ms_40cm、Ms_80cm、Ms_120cm、Ms_200cm、Ms_300cm、Ms_500cm) (%, volumetric water content). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2018/8/31 10:30. Moreover, suspicious data were marked in red.

0 2022-06-29

Seasonally frozen ground soil temperature and moisture data set of alpine meadow site in Qinghai Lake Basin(2018-2021)

This dataset is a high-frequency observation data of soil temperature and humidity in the active layer of seasonal frozen soil observed in the alpine meadow of Qianhuli Small watershed of Qinghai Lake, with a time resolution of half an hour. The data set can provide data support for the rate-dependent soil hydrothermal model and dynamic characterization of soil active layer.

0 2022-05-26

Vegetation environmental research data set in key areas of Qilian-Altun Mountain area of Qinghai Tibet Plateau (2021)

This data set includes 4 data files, which are: (1) Land use survey data set_ Qilian - Altun Mountain (2021), including 31 survey points at the Qilian - Altun Mountain land use survey data, including survey time, location, latitude and longitude, altitude, slope aspect, main vegetation types and dominant species. (2) chlorophyll content of dominant species data_ Qilian - Altun Mountain (2021), including the chlorophyll content of dominant species in 31 investigation points of Qilian- Altun area. Five leaves are selected for each plant to measure the chlorophyll content in the upper, middle and lower parts of the leaves; (3) Leaf area index survey data _ Qilian - Altun Mountain (2021), including the survey data and calculated average value of leaf area index of main vegetation types at 31 survey points in Qilian-Altun area, the data was measured by SunScan canopy analyzer; (4) Survey data of soil temperature and humidity _ Qilian - Altun Mountain (2021), including longitude and latitude, altitude, soil surface temperature and soil humidity at 30cm of 31 survey points in Qilian-Altun area, the data are recorded as three repeated measurements at each survey point. This data set can be used to analyze and study the law of vegetation environmental change on the Qinghai Tibet Plateau.

0 2022-01-20

Comprehensive observation system for carbon dioxide isotopes during soil biochemistry process: multichannel and dual-cycle observation system for soil CO2 and δ13C fluxes (2019-2020)

Soil respiration is the second most important carbon flux, which is only lower than that of photosynthesis in terrestrial ecosystems. The production and transport of CO2 and its δ13C by soil biochemical processes are the limiting factors for the magnitude and process evaluation of soil respiration. According to the characteristics of CO2 gas generation and transportation in soil biochemical process, based on stable isotope infrared spectroscopy technology, the nonlinear on-line calibration technology, multi-channel double-cycle efficient gas circulation path, efficient gas circulation path with pre-reduced gas concentration, and variable temperature technology that can simulate the freezing and thawing process were independently developed. On account of the gas exchange process in soil and air interface, vertical migration process of CO2 in soil profile and the process of soil organic matter decomposition, we develop a comprehensive observation system for measuring the isotope composition of carbon dioxide during soil biochemistry processes. The observation systems were placed in the ecologically fragile areas and measured the concentration and flux of soil CO2 and its δ13C, which effectively solved the comprehensive monitoring problem in generation, migration and release of CO2 during soil biochemical process. (1) a multichannel and dual-cycle observation system for soil CO2 and δ13C fluxes at the soil-atmosphere interface: We developed an online calibration system for the nonlinear response of CO2 and its δ13C analyzer at multiple concentrations to ensure the accuracy and accuracy of the instrument. By controlling the circuit switch, the instrument can automatically switch and collect circular observations between multiple channels. By controlling the premixing of gas in the channel while waiting to collect an observation, the instrument can decrease the observation time required for every channel and increase the efficiency and frequency of observation collection. By premixing the gas in the channel to be monitored, the instrument can eliminate the “dead gas” disturbances in the observation results and improve the accuracy of the observations. Based on the simulation flux verification system test, the simulated flux of CO2 and δ13C is better than 0.32 μmol m-2 s-1 @ 10 μmol m-2 s-1 (CO2) and 0.52‰ @ 10 μmol m-2 s-1 (CO2), which is better than the core technical index requirements of the project. The average domestication rate of the equipments is more than 80%, which has been used in the automatic monitoring of forest, grassland and farmland ecosystems, realizing the independent innovation and upgrading of ecological monitoring technology in China, and can be extended to CERN, CFERN, CNERN and similar field stations in other related departments. It is helpful to greatly improve China's R&D capability, level and international influence on ecological monitoring and assessment, effectively support China's terrestrial ecosystem carbon sequestration rate and potential assessment and certification, and provide technical support for national ecological civilization construction, carbon peak, carbon neutrality and ecological security regulation.

0 2021-11-17

WATER: Dataset of the automatic meteorological observations at the Pailugou grassland station in the Dayekou watershed (2008-2009)

The dataset of the automatic meteorological observations (2008-2009) was obtained at the Pailugou grassland station (E100°17'/N38°34', 2731m) in the Dayekou watershed, Zhangye city, Gansu province. The items included multilayer (1.5m and 3m) of the air temperature and air humidity, the wind speed (2.2m and 3.7m) and direction, the air pressure, precipitation, the global radiation, the net radiation, co2 (2.8m and 3.5m), the multilayer soil temperature (10cm, 20cm, 40cm, 60cm, 120cm and 160cm), soil moisture (10cm, 20cm, 40cm, 60cm, 120cm and 160cm), and soil heat flux (5cm, 10cm and 15cm). For more details, please refer to Readme file.

0 2021-03-10

Multi-scale surface flux and meteorological elements observation dataset in the Hai River Basin (Huailai station-automatic weather station-10m tower, 2015)

The data set contains the observation data of the 10m tower automatic meteorological station on December 31, 2015 on January 1, 2015 at solstice.The station is located in east garden town, huailai county, hebei province.The latitude and longitude of the observation point is 115.7880E, 40.3491N, and the altitude is 480m. The automatic weather station is installed on a 10m tower, the acquisition frequency is 30s, and the output time is 10min.The observation factors include air temperature and relative humidity (5m), and the direction is due north.The wind speed (10m), the wind direction (10m), the direction is due to the north;Air pressure (installed in waterproof box);Rainfall (10m);The four-component radiation (5m), the direction is due to the south;The infrared surface temperature (5m), the arm is facing south, and the probe is facing vertically downward.The soil temperature and humidity probe was buried at 1.5m to the south of the meteorological tower. The buried depth of the soil temperature probe was 0cm, 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm. The buried depth of the soil moisture sensor was 2cm, 4cm, 10cm, 10cm, 10cm, 10cm, 20cm, 80cm, 120cm and 160cm.The average soil temperature was buried 2,4 cm underground.Soil hot flow plates (3) are buried in the ground 6cm. Processing and quality control of observation data :(1) ensure 144 data per day (every 10min). If data is missing, it will be marked by -6999;(2) eliminate the moments with duplicate records;(3) data that is obviously beyond the physical meaning or the range of the instrument is deleted;(4) the format of date and time is unified, and the date and time are in the same column.For example, the time is: 10:30 on June 10, 2015.Data missing due to damage of charging controller from May 30 to June 5 and October 1 to October 9.Soil heat flux G1 due to the heat flux plate problem, the data of April 19 solstice on May 20 was missing. Data released by the automatic weather station include:Date/Time, air temperature and humidity observation (Ta_5m, RH_5m) (℃, %), wind speed (Ws_10m) (m/s), wind direction (WD) (°), pressure (hpa), precipitation (Rain) (mm), four-component radiation (DR, UR, DLR, ULR, Rn) (W/m2), surface radiation temperature (IRT_1, IRT_2) (℃),Soil heat flux (Gs_1, Gs_2, Gs_3) (W/m2), multi-layer soil moisture (Ms_2cm, Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_80cm, Ms_120cm, Ms_160cm) (%), multi-layer soil temperature (Ts_2cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm) (℃), average soil temperature TCAV (℃). Please refer to Guo et al. (2020) for information of observation test or site, and Liu et al. (2013) for data processing.

0 2020-10-28

Multi-scale surface flux and meteorological elements observation dataset in the Haihe River Basin (Huailai station-automatic weather station-10m tower, 2014)

The dataset contains the observation data of the 10m tower automatic weather station on January 13, 2014 at solstice on December 31, 2014.The station is located in east garden town, huailai county, hebei province.The latitude and longitude of the observation point is 115.7880E, 40.3491N, and the altitude is 480m. The automatic weather station is installed on a 10m tower, the acquisition frequency is 30s, and the output time is 10min.The observation factors include air temperature and relative humidity (5m), and the direction is due north.The wind speed (10m), the wind direction (10m), the direction is due to the north;Air pressure (installed in waterproof box);Rainfall (10m);The four-component radiation (5m), the direction is due to the south;The infrared surface temperature (5m), the arm is facing south, and the probe is facing vertically downward.The soil temperature and humidity probe was buried 1.5m south of the meteorological tower. The soil temperature probe was buried at a depth of 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm. The soil moisture sensor was buried at a depth of 2cm, 4cm, 10cm, 20cm, 80cm, 120cm and 160cm.The average soil temperature was buried 2,4 cm underground.Soil hot flow plates (3) are buried in the ground 6cm.Processing and quality control of observation data :(1) ensure 144 data per day (every 10min). If data is missing, it will be marked by -6999;(2) eliminate the moments with duplicate records;(3) data that is obviously beyond the physical meaning or the range of the instrument is deleted;(4) the format of date and time is unified, and the date and time are in the same column.For example, the time is: 2014-6-10-10:30.January 13 - March 26 due to probe problems, soil moisture data at a depth of 20cm was wrong;From January 21 to March 26, due to probe problems, soil moisture data at a depth of 120cm was wrong;From March 17 to March 26 due to probe problems, soil moisture data at depth of 2,4,10,20 cm were wrong.The soil heat flux G2 had a problem on June 16, BBB 0, July 9 due to the hot plate problem. Guo et al, 2020 is used for site introduction and Liu et al, 2013 for data processing

0 2020-10-27